This invention relates generally to power plant water systems. More particularly, this invention relates to an automated system for screening and analyzing power plant water chemistry data to diagnose power plant water chemistry problems.
Many power plants operate by heating water to produce steam. The steam is then used to drive a turbine. The turbine rotates a generator that is used to produce electricity.
The water chemistry in power plants of this type is typically monitored at several locations within the system. Trend graphs are then constructed using the collected chemistry data. Trained chemistry personnel review the data to insure that the impurity and additive levels are within prescriptive specifications and to identify underlying trends in the data which may indicate abnormal operation of the system.
Data acquisition systems have been developed for collecting and displaying power plant water chemistry data. Rule based expert systems have also been developed to identify inconsistencies in the data and warn of possible abnormal conditions. Existing expert systems are limited to rudimentary analyses of chemistry data.
It would be highly desirable to improve existing prior art techniques of analyzing power plant water chemistry. In particular, it would be highly desirable to provide an automated technique for improving the reliability of power plant water chemistry data. In addition, it would be highly desirable to provide an automated technique for assessing power plant water chemistry data to diagnose problems therein.
The invention is a power plant water chemistry analysis apparatus and method. The apparatus relies upon water chemistry sensors to obtain power plant water chemistry data characterizing the chemical activity of a power plant water system. An analytical model processor is used to generate model predictions for the power plant water system. A statistical data fitting processor selects screened data from the power plant water chemistry data that corresponds to the model predictions. The screened data is processed by an artificial intelligence processor to derive plant water chemistry diagnostic information. The artificial intelligence processor includes an expert system, rule base, plant water chemistry system simulator, and pattern recognition module.
The invention is used to diagnose normal and abnormal conditions in power plant water systems. Alone, or in conjunction with on-line data acquisition systems, the invention is used to minimize the amount of data which must be collected to properly account for the chemical state of the power plant water system. The invention greatly reduces costs associated with both instrumentation and the staffing required to maintain a water chemistry program. The system also provides information on the chemical state of the system in locations where measurements cannot be easily or economically made. This information is used in conjunction with knowledge of the degradation of system materials to minimize the impact of chemical action on power plant operation.